Abstract
Purpose
This article analyses the trend in women digital financial inclusion in Nigeria using some digital financial inclusion indicators obtained from the global Findex database for the year 2014, 2017 and 2021. The study also analyses the relationship between women digital financial inclusion and economic growth.
Design/methodology/approach
The data were analysed using the two-stage least squares (2SLS) and generalised method of moments (GMM) regression estimation methods. The women digital financial inclusion indicators are the percentage of women who (1) own a mobile money account, (2) made a digital payment, (3) received digital payments, (4) made or received a digital payment, (5) own a credit card and (6) own a debit card.
Findings
The trend analysis shows a sustained, although small, improvement in women mobile money account ownership during the period, while the other indicators witnessed a decrease in 2017 and an increase in 2021, except for women credit card ownership which remained at the same level during the period examined. There is a significant positive relationship between women digital financial inclusion and economic growth. Internet usage has a significant positive effect on women digital financial inclusion in Nigeria.
Practical implications
Greater digital financial inclusion for women can accelerate economic growth in Nigeria. Policymakers should encourage investment in fintech and broaden access to the Internet to increase women digital financial inclusion and economic growth in Nigeria. Policymakers and practitioners in Nigeria should also work collaboratively to increase digital financial inclusion for women due to its potential to increase economic growth in Nigeria.
Originality/value
Existing studies did not analyse the trends in women digital financial inclusion. Existing studies did not empirically analyse the impact of women digital financial inclusion on economic growth in Nigeria. The present study fills this gap in the literature.
Keywords
Citation
Ozili, P.K. (2024), "Women digital financial inclusion and economic growth in Nigeria", Journal of Internet and Digital Economics, Vol. 4 No. 3, pp. 161-178. https://doi.org/10.1108/JIDE-07-2024-0027
Publisher
:Emerald Publishing Limited
Copyright © 2024, Peterson K. Ozili
License
Published in Journal of Internet and Digital Economics. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Digital financial inclusion simply means achieving financial inclusion using digital technology. It refers to using fintech, bigtech, blockchain and other digital technologies to expand access and use of formal financial services to a large segment of the population (Shen et al., 2021; Xun et al., 2020). Digital financial inclusion is also viewed as digital access to, and use of, formal financial services by the unbanked and underserved population. Digital financial inclusion is considered to be a game changer in the quest to achieve high levels of financial inclusion (Shen et al., 2021; Ozili, 2022). It offers several benefits including access to additional financial services such as insurance, mortgage and investment products.
To achieve digital financial inclusion, there must be five elements: a digital transactional platform, retail agents, a device, additional financial services offered through the digital transactional platform and the regulator who will introduce safeguards. However, having these five elements may not guarantee successful digital financial inclusion if there is low usage of digital financial services. This implies that widespread use of digital financial services is essential for successful digital financial inclusion. Despite the widespread advocacy for digital financial inclusion especially in developing countries, digital financial inclusion is still very low in many developing countries due to low awareness, digital illiteracy, financial illiteracy and lack of trust in digital finance technology.
In Nigeria, the rate of digital financial inclusion is increasing even though it still falls short of Nigeria’s 2018 National Financial Inclusion Strategy (NHIS). There is also a gender gap in financial inclusion with women experiencing low levels of financial inclusion in Nigeria due to financial illiteracy and lack of awareness about available formal financial services. Most of Nigeria’s effort to increase financial inclusion have focused on agent banking and the deployment of fintech and payment service agents. In 2018, the central bank licenced payment service banks (PSBs) to offer only digital payments but not loans. In 2019, the central bank introduced the Shared Agent Network Expansion Facilities (SANEFs) in partnership with commercial banks to increase the number of financial access points in the country and to provide a platform to open a bank account at any agent location in Nigeria. In 2022, the central bank increased licencing for mobile money operators (MMOs). The central bank has also launched several initiatives to increase women financial inclusion, but these initiatives have not closed the gender gap in digital financial inclusion in Nigeria. For example, the 2021 global Findex data for Nigeria shows that female mobile money account ownership accounted for 5% of the population compared to male mobile money account ownership at 12%. The percentage of women who made or received a digital payment was 23% compared to men at 43%. Also, the percentage of women who made a digital in-store merchant payment was only 4% compared to 7% for the male population, while the percentage of women who used a mobile phone or the Internet to buy something online was 3% compared to 4% for the male population. These statistics show that women digital financial inclusion in Nigeria is low, and it calls for a closer look at the trends in women digital financial inclusion in Nigeria, to identify the trends in women digital financial inclusion and the opportunities for growth both in the digital financial inclusion indicators and for the Nigerian economy. Therefore, this study analyses the trend in women digital financial inclusion in Nigeria using six digital financial inclusion indicators obtained from the global Findex database for the year 2014, 2017 and 2021. The study also analyses the relationship between women digital financial inclusion and economic growth.
In the literature, few existing Nigerian studies have analysed digital financial inclusion from a narrow perspective without examining the digital financial inclusion of women in Nigeria. For example, Wayne et al. (2020) showed that banks, fintech, and mobile money agents are using technology to close the gap in financial inclusion by reducing the cost of providing financial services. Ozili (2023) showed that Nigeria’s central bank digital currency is also helping to increase digital financial inclusion in Nigeria by reducing the barriers to account ownership and reducing transaction cost. Meanwhile, Wezel and Ree (2023) argued that although Nigeria has made some progress in digital financial inclusion, Nigeria still has a gender gap and there is a need to improve digital and financial literacy, upgrade digital infrastructure and promote sound practices of fintech firms to significantly increase digital financial inclusion in Nigeria. Igwemeka et al. (2020) also argued that the digital financial inclusion problem in Nigeria is not just a Nigerian problem, as other developing countries are also faced with low levels of digital financial inclusion. While these studies have focused on digital financial inclusion in Nigeria, these studies did not examine women financial inclusion in Nigeria. These studies did not present a detailed analysis of the trends in women digital financial inclusion, and they did not empirically analyse the potential effect of women digital financial inclusion on economic growth in Nigeria. The present study fills this gap in the literature.
In the empirical analysis, the data are analysed using the two-stage least squares (2SLS) and the generalised method of moments (GMM) estimation methods which address endogeneity problems in the data. The findings show a significant positive relationship between the women digital financial inclusion indicators and economic growth, except for the women mobile money account ownership indicator. The findings also show that internet usage has a significant positive effect on women digital financial inclusion in Nigeria, indicating that the use of internet is crucial to increase women financial inclusion in Nigeria.
This study contributes to the literature by focussing on financial inclusion for women. There is very little research focussing on women financial inclusion in Africa, much less women digital financial inclusion in Nigeria. This study is the first to focus on the trends in digital financial inclusion for women. The study also contributes to the literature by linking women digital financial inclusion to economic growth. The study aims to gain insight into whether improvements in women digital financial inclusion could stimulate economic growth in Nigeria.
The remainder of the study is organised as follows. Section 2 presents the review of existing studies. Section 3 presents the data and method. Section 4 presents the discussion of results, while Section 5 presents the conclusion of the study.
2. Literature review
Several studies have investigated the developments in digital financial inclusion. For example, Wezel and Ree (2023) showed that Nigeria has made progress in digital financial inclusion, but the level of digital financial inclusion in Nigeria is lower than that of its peers. They argued that Nigeria can achieve further successes if there is significant improvement in financial literacy, upgrade of digital infrastructure, the adoption of sound fintech practices, and the use of digital financial services especially mobile money and central bank digital currency. Ozili (2018) showed that digital financial services offer convenience and low-cost financial services to low-income individuals. Koh et al. (2018) focused on the status of digital financial inclusion in Southeast Asia. They examined the developments in digital financial inclusion in Southeast Asia from 2011 to 2014 and using data from the global Findex database. They found a wide variation in access and use of bank accounts and wide differences in the level of development of banking sector technology infrastructure.
Several studies focused on the factors encouraging women digital financial inclusion and the effect of women digital financial inclusion. For instance, Ozili (2024) argued that women are at risk of financial exclusion because they are vulnerable group; for this reason, digital financial inclusion efforts should be targeted at women to ensure that women have access to the digital financial services they need to improve their welfare. Ojo (2022) was concerned about the marginalisation of women and girls in African countries and was curious to determine whether digital financial inclusion can help to reduce women marginalisation and increase women empowerment in African countries. Ojo (2022) examined the role of digital financial inclusion in women’s economic empowerment in Ghana, Kenya, Namibia and Lesotho. The author found that the introduction of gender equity in the digital economy increased women digital financial inclusion and women empowerment in African countries. Mabrouk et al. (2023) considered how digital financial inclusion might affect the economic empowerment of women in Saudi Arabia using data obtained from the global Findex database from 2017 to 2021. They sought to compare the impact of digital financial inclusion on women economic empowerment before and after the COVID-19 pandemic. They found that digital financial inclusion increased during the COVID-19 pandemic in 2021 and digital financial services increased women empowerment in Saudi Arabia. In a related study, Elouardighi and Oubejja (2023) were interested in the relationship between digital financial inclusion and the participation of women in the labour force to ascertain whether digital financial inclusion can reduce the gender disparity in the labour market. They analysed micro-level data of 15,192 women from 29 African countries in 2021. They analysed women data using the Probit model estimation method and found that women digital financial inclusion increased the participation of women in the labour force.
Yang et al. (2022) were interested in whether digital financial inclusion can improve women entrepreneurship. They focused on some regions in China and examined the effect of regional digital financial inclusion on female entrepreneurship in China. They found that digital financial inclusion has a significant positive impact on women entrepreneurial behaviour. It was also found that digital financial inclusion increased access to financial services, and it alleviates the information constraints that hinder women’s access to financial services in China. Kulkarni and Ghosh (2021) were concerned about the barriers women face in accessing and using digital financial services in India. They wanted to gain insights into the gender disparity in the digitalisation of financial services and how it affects women. In their study, they found that the gender disparity in digital financial inclusion is not influenced by the level of economic development. They also found that digitalisation increased the social and financial autonomy of women in India. Setiawan et al. (2024) examined the factors hindering the adoption of fintech among women in Indonesia. They surveyed 409 Indonesian female respondents and found that the factors that determine women’s intention to adopt fintech products are perceived usefulness, user innovativeness, brand, attitude and trust. It was also found that perceived ease of use, financial literacy and government support do not influence women’s intention to adopt fintech products in Indonesia. Zhao and Jiao (2024) examined the effect of digital financial inclusion on regional innovation and common prosperity in China. They examined 31 provinces over the 2011 to 2021 period. Using a structural equation model, they found that digital financial inclusion has a positive impact on common prosperity in the Eastern provinces in China but not in the western provinces. They also found that the level of regional innovation moderates the impact of digital financial inclusion on common prosperity in China. They conclude by proposing that efforts should be made to improve digital financial inclusion and regional innovation to foster greater common prosperity in China.
Other studies examined the effect of digital financial inclusion on economic growth. For example, Ahmad et al. (2021) noted the rapid expansion of digital financial inclusion in China and were interested in determining whether the rapid rise in digital financial inclusion has a positive impact on economic growth in China. They examined whether digital financial inclusion and human capital affect provincial economic growth in China. Their results showed that digital financial inclusion and human capital affect provincial economic growth in China. In a related study, Xun et al. (2020) were interested in determining whether digital finance driven by the internet revolution helps to promote economic growth in China. They constructed a digital financial inclusion index using the China Family Panel Studies (CFPSs) survey and examined whether digital finance promotes inclusive growth in China. They found that digital finance improved household income in China. Another related study, Liu et al. (2021) used a Bayesian macroeconomic analysis framework to examine the impact of digital financial inclusion on economic growth in China from 2011 to 2019. Interestingly, they found that digital financial inclusion has a significant impact on China’s economic growth. They also found that there is a threshold effect which means that digital financial inclusion increased economic growth up to a level after which further increases in digital financial inclusion decreased economic growth. They also found that small and medium-sized enterprises (SMEs) is the main channel through which digital financial inclusion contributes to economic growth in China.
In a cross-country study, Ozturk and Ullah (2022) were interested in determining whether digital financial inclusion contributes to economic growth and environmental quality. Ozturk and Ullah (2022) analysed the effect of digital financial inclusion on economic growth and environmental sustainability in 42 One Belt Road Initiative (OBRI) countries from 2007 to 2019. The data used in the study was analysed using the ordinary least squares (OLSs), 2SLS and GMMs regression methods. They found that digital financial inclusion increased economic growth but decreased environmental quality through a reduction in CO2 emissions. In a related study, Shen et al. (2021) developed a digital financial inclusion index and used the index to analyse the effect of digital financial inclusion on economic growth using spatial data of 85 countries. They conducted a spatial analysis and found that digital financial inclusion has a significant positive impact on economic growth, and it also has a spatial spillover effect on neighbouring countries. Khera et al. (2021) argued that digital financial services may stimulate economic growth in some countries and may fail to stimulate economic growth in other countries. They evaluate their argument by conducting a cross-country analysis of the impact of digital financial services on economic growth in 52 developing countries. They found that digital financial inclusion accelerates economic growth, and the key drivers of digital financial inclusion across countries are access to infrastructure, financial literacy, digital literacy and the quality of institutions.
Daud and Ahmad (2023) noted the upsurge in financial inclusion and digital technologies in many countries since the global financial crisis. Daud and Ahmad (2023) examined the relationship between digital financial inclusion and economic growth in 84 countries after the global financial crisis period. They showed that digital financial inclusion has a significant positive effect on economic growth in the post crisis period. The author also found that digital technology complements the positive effect of financial inclusion on economic growth, implying that digital technology infrastructure can enhance the contribution of financial inclusion to economic growth across countries. Chinoda and Kapingura (2024) examined whether institutional quality influences the relationship between digital financial inclusion and economic growth in Sub-Saharan Africa from 2014 to 2020. They found that institutional quality has a positive moderating effect on the relationship between digital financial inclusion and economic growth in sub-Saharan African countries. Rekha et al. (2021) examined the relationship between digital financial inclusion, economic freedom, financial development and economic growth. They found that information and communication technology (ICT) diffusion has a positive impact on financial inclusion in the long run. Thaddeus et al. (2020) examined the long run causal impact of digital financial inclusion on economic growth in 22 sub-Saharan African countries from 2011 to 2017. They found a long-run causal relationship between digital financial inclusion and economic growth in sub-Sahara Africa and the direction of causality is unidirectional running from economic growth to digital financial inclusion.
Ugwuanyi et al. (2022) analysed the impact of financial inclusion on economic growth. They examined 29 sub-Saharan African countries from 2012 to 2020. They disaggregate the financial inclusion indicators into traditional finance and digital finance indicators and estimate the data using the feasible generalised least squares, the system GMM, the vector autoregression and Granger causality test methods. They found that digital financial inclusion has a significant positive impact on economic growth. They also found that both the traditional and digital financial inclusion indicators have a significant positive effect on economic growth, but the traditional financial inclusion indicators have a more significant impact than the digital financial inclusion indicators. They further found that the effect of the traditional and digital financial inclusion indicators on economic growth differ across income levels. Banna (2020) argued that digital financial inclusion may lead to negative and positive effects on economic growth in the 4th Industrial Revolution especially in Bangladesh. They examined the role of digital financial inclusion in promoting sustainable economic growth in Bangladesh from 2011 to 2018 and found that digital financial inclusion has a positive impact on economic growth, and the channel through which this happens is through banks.
While these studies examine the relationship between digital financial inclusion and economic growth, the literature has not extensively examined the relationship between digital financial inclusion and economic growth in Nigeria. The literature has also not examined the relationship between women digital financial inclusion and economic growth in Nigeria. This study will fill this gap in the literature.
3. Data and method
Annual digital financial inclusion data for Nigeria were collected from the World Bank's global Findex database. Economic growth data were collected from the World Development Indicators (WDIs) of the World Bank. The sample period covers only 2014, 2017 and 2021. See Table 1 for variable description. The data were estimated using the 2SLS regression and the Arellano–Bond first-difference GMM regression methodology. These two regression methods were used to address endogeneity problems in the data. Table 2 presents the Pearson correlation analysis for digital financial inclusion and economic growth. It presents the correlation between the women who own a mobile money account (MMA), women who made or received a digital payment (MRP), women who made a digital payment (MP), women who received a digital payment (MR), women who own a debit card (DD) and economic growth (GDPR). The p-values are reported in parenthesis. The correlation matrix in Table 2 reports a high positive correlation between MRP and MR. It also shows a high positive correlation between MPs and DD. A possible explanation for this result is that Nigerian women who own a debit card also used their debit card to make digital payments. There is also a positive correlation between MP and MR. A possible explanation for this result is that the women that own a debit card also used their debit card to receive digital payments. In contrast, the GDPR and DD variables have a high negative correlation of −0.993. This indicates that there is a high inverse correlation between GDPR and DD. This suggests that greater women debit card ownership is not associated with higher economic growth. Also, the GDPR and MP variables have a high negative correlation of −0.901. This indicates that there is a high inverse correlation between GDPR and the MP. This suggests that greater digital payments by women is not correlated with higher economic growth. Also, the MMA and MRP variables have a high negative correlation of −0.737. This indicates that there is a high inverse correlation between MMA and the percentage of MRP. This suggests that greater ownership of mobile money account by women may not increase the percentage of women who make or receive digital payments. Also, the GDPR and MP variables have a high negative correlation of −0.901. This indicates that there is a high inverse correlation between the percentage of women that made MPs and GDPR. This suggests that greater digital payments made by women is not associated with higher economic growth. In terms of statistical significance based on the p-value, the correlation result shows a significant positive correlation between MRPs and MR. The correlation result also shows a significant negative correlation between GDPR and DD. This implies that greater women debit card ownership is significantly associated with lower economic growth.
4. Discussion
4.1 Trend analysis of the women digital financial inclusion indicators
Regarding women mobile money account ownership, the data in Figure 1 shows that mobile money account ownership for women improved marginally over the years. It increased from 2%, 4 and 5% in 2014, 2017 and 2021, respectively. The improvement in mobile money account ownership was due to the efforts of the central bank to increase digital financial inclusion for women in Nigeria. The central bank facilitated the deployment of agent banking networks and point-of-sale (POS) terminals to all communities across the country which enabled women to have easy access to a POS agent, mobile financial services and to own a mobile money account.
Regarding women that received digital payments, the data in Figure 1 shows a marginal decline in 2017 and a recovery in 2021. Women that received digital payments decreased from 20% in 2014 to 16% in 2017 and increased to 18% in 2021. The decline witnessed in 2017 was due to women’s lack of trust in digital payment platforms. Nigerian women had little trust in digital payment platforms due to fraud concerns. However, the introduction of a strong consumer protection framework by the central bank increased women’s trust in using digital platforms to receive money. This led to increased trust in digital financial services among women and led to a 18% increase in the percentage of women that received digital payments. During the COVID-19 pandemic, many women became comfortable with receiving payments through digital platforms because of the convenience and efficiency it offered.
Regarding women that made digital payments, the data in Figure 1 shows a marginal decline in 2017 and a recovery in 2021. Women that made digital payments decreased from 20% in 2014 to 17% in 2017 and increased to 20% in 2021. The decline witnessed in 2017 was also due to women’s lack of trust in digital payment platforms. Nigerian women had little trust in digital payment platforms due to fraud concerns. However, the introduction of a strong consumer protection framework by the central bank increased people’s trust in using digital platforms to send money. This led to increased trust in digital financial services among women and led to a 20% increase in the percentage of women that make digital payments in 2021. During the COVID-19 pandemic, many women became comfortable with making payments through digital devices because of the convenience and efficiency it offered.
Regarding women that made or received digital payments, the data in Figure 1 shows a decline in 2017 and a slight recovery in 2021. Women that made or received digital payments decreased from 26% in 2014 to 21% in 2017 and increased to 23% in 2021. The decline witnessed in 2017 was also due to a general distrust in digital payment platforms. Nigerian women had little trust in digital payment platforms due to fraud concerns. However, the introduction of a strong consumer protection framework by the central bank increased women’s trust in using digital platforms to make and receive money. This led to increased trust in digital financial services among women and led to a 23% increase in the percentage of women that make or receive digital payments. During the COVID-19 pandemic, many women became comfortable with making or receiving payments through digital devices because of the convenience and efficiency it offered.
Regarding women that own a credit card, the data in Figure 1 shows that only 2% of Nigerian women own a credit card between 2014 and 2021. This low number was due to women not being aware that they can own a credit card. It could also be due to the Nigerian culture that discourages households from taking loans from formal financial institutions. Therefore, many women were not interested in owning credit cards because they do not want to be perpetually indebted to financial institutions if they are unable to repay their debt on time.
Regarding women that own a debit card, the data in Figure 1 shows a decline in women debit card ownership in 2017 and an increase in 2021. Women that own a debit card decreased from 25% in 2014 to 23% in 2017 and increased to 26% in 2021. The decline witnessed in 2017 was due to three factors such as women’s lack of awareness of debit cards, excessive debit card charges and a general lack of interest in debit cards among women. However, in 2020, the central bank introduced policies to regulate bank debit card fees. The purpose of the regulation was to ensure that debit card charges are low and affordable for debit card users. The regulation prohibited banks from imposing unexplained and excessive debit or credit card charges. The regulation encouraged more women to own a debit card especially during the 2020–2021 COVID-19 pandemic, and this was reflected in the 26% increase in women debit card ownership in 2021.
4.2 Graphical analysis of the relationship between women digital financial inclusion and economic growth
Regarding women mobile money account ownership, Figure 2 shows a negative relationship between women mobile money account ownership and economic growth from 2014 to 2017. There is a positive relationship between women mobile money account ownership and economic growth from 2017 to 2021. The increase in women mobile money account ownership was associated with increase in economic growth from 2017 to 2021 and suggests that women mobile money account ownership partly contributed to economic growth in Nigeria in 2017 and 2021. Regarding women that made or received digital payments, Figure 3 shows a positive relationship between women that made or received digital payments and economic growth. This indicates that an increase (decrease) in the percentage of women that made or received digital payments was associated with increase (decrease) in economic growth during the period. Regarding women that made digital payments, Figure 4 shows a positive relationship between women that made digital payments and economic growth. This indicates that an increase (decrease) in the percentage of women that made digital payments was associated with increase (decrease) in economic growth during the period. Regarding women that received digital payments, Figure 5 shows a positive relationship between women that received digital payments and economic growth. This indicates that an increase (decrease) in the percentage of women that received digital payments was associated with increase (decrease) in economic growth during the period. Regarding women debit card ownership, Figure 6 shows a positive relationship between women debit card ownership and economic growth. This indicates that increase (decrease) in women debit card ownership was associated with increase (decrease) in economic growth during the period. Regarding women credit card ownership, Figure 7 shows that credit card ownership among Nigerian women remained at the same level throughout the period despite the fluctuations in economic growth. This suggests that women credit card ownership or its usage does not influence economic growth in Nigeria.
4.3 Regression analysis for the impact of digital financial inclusion on economic growth
4.3.1 Two-stage least squares estimation
This section examines the direct impact of women digital financial inclusion on economic growth in Nigeria using a univariate 2SLS regression method. The 2SLS regression estimation helps to address any endogeneity problems in the data.
The result reported in Table 3 shows that the MR variable has a positive coefficient and is significantly related to the GDPR variable in the 2SLS estimation. This indicates that an increase in the percentage of women who receive digital payments leads to higher economic growth in Nigeria. This implies that the women who receive digital payments contribute significantly to economic growth in Nigeria. This result also supports the studies that show evidence that digital financial inclusion has a significant positive effect on economic growth (e.g. Ahmad et al., 2021; Shen and Hueng, 2021; Khera et al., 2021). The MRP variable also has a positive coefficient and is significantly related to the GDPR variable in the 2SLS estimation in Table 3. This indicates that an increase in the percentage of women who make or receive digital payments leads to higher economic growth in Nigeria. This implies that the women who make or receive digital payments contribute significantly to economic growth in Nigeria. This result also supports the studies that show evidence that digital financial inclusion has a significant positive effect on economic growth (e.g. Ahmad et al., 2021; Shen and Hueng, 2021; Khera et al., 2021).
In contrast, the MMA variable has an insignificant effect on economic growth in the 2SLS estimation in Table 3. The MP variable also has an insignificant effect on the GDPR variable in the 2SLS estimation in Table 3. These two results do not support the studies that show evidence that digital financial inclusion has a significant effect on economic growth (e.g. Ahmad et al., 2021; Shen and Hueng, 2021; Khera et al., 2021). The DD variable is also insignificantly related to the GDPR variable in the 2SLS estimation in Table 3. This result does not support the studies that show evidence that digital financial inclusion makes a significant contribution to economic growth (e.g. Ozili, 2018; Liu et al., 2022; Lv et al., 2022). The CC variable is also insignificantly related to the GDPR variable in the 2SLS estimation in Table 3. This result does not support the studies that show evidence that digital financial inclusion makes a significant contribution to economic growth (e.g. Ozili, 2018; Liu et al., 2022; Lv et al., 2022).
4.3.2 Arellano–Bond GMM estimation
This section examines the direct impact of women digital financial inclusion on economic growth in Nigeria using a univariate Arellano–Bond first-difference GMM regression method. The GMM regression estimation also addresses any potential endogeneity problems in the data. The result reported in Table 4 shows that the MMA variable has a positive coefficient and an insignificant effect on economic growth in the GMM estimation. The MP variable has a positive coefficient and is significantly related to the GDPR variable in the GMM estimations in Table 4. This indicates that an increase in the percentage of women who make digital payments leads to higher economic growth in Nigeria. This implies that the women who make digital payments contribute significantly to economic growth in Nigeria. This result supports the studies that show evidence that digital financial inclusion makes a significant contribution to economic growth (e.g. Ahmad et al., 2021; Shen and Hueng, 2021; Khera et al., 2021). The MR variable also has a positive coefficient and is significantly related to the GDPR variable in the GMM estimation in Table 4. This indicates that an increase in the percentage of women who receive digital payments leads to higher economic growth in Nigeria. This implies that the women who receive digital payments contribute significantly to economic growth in Nigeria. This result also supports the studies that show evidence that digital financial inclusion significantly contributes to economic growth (e.g. Ahmad et al., 2021; Shen and Hueng, 2021; Khera et al., 2021). The MRP variable also has a positive coefficient and is significantly related to the GDPR variable in the GMM estimation in Table 4. This indicates that an increase in the percentage of women who make or receive digital payments leads to higher economic growth in Nigeria. This implies that the women who make or receive digital payments contribute significantly to economic growth in Nigeria. This result also supports the studies that show evidence that digital financial inclusion significantly contributes to economic growth (e.g. Ahmad et al., 2021; Shen and Hueng, 2021; Khera et al., 2021). The DD variable also has a positive coefficient and is significantly related to the GDPR variable in the GMM estimation in Table 4. This indicates that an increase in the percentage of women who own a debit card leads to higher economic growth in Nigeria. This implies that the women who own a debit card contribute significantly to economic growth in Nigeria. This result supports the studies that show evidence that digital finance products contribute significantly to economic growth (e.g. Ozili, 2018; Liu et al., 2022; Lv et al., 2022). The CC variable also has a positive coefficient and is significantly related to the GDPR variable in the GMM estimation in Table 4. This indicates that an increase in the percentage of women who own a credit card leads to higher economic growth in Nigeria. This implies that the women who own a credit card contribute significantly to economic growth in Nigeria. This result supports the studies that show evidence that digital finance products contribute significantly to economic growth (e.g. Ozili, 2018; Liu et al., 2022; Lv et al., 2022).
4.3.3 Further analysis
An additional analysis is conducted after introducing the Internet usage variable as a control variable into the baseline model. The result is reported in columns 1 to 6 of Tables 5 and 6. The MMA, MP, MR, MRP, DD and CC variables are insignificant in the 2SLS and GMM estimations in Tables 5 and 6 This indicates that the women digital financial inclusion indicators have an insignificant effect on economic growth. Similarly, the INT variable is insignificant in the 2SLS and GMM estimations in Tables 5 and 6. This indicates that the percentage of people using the Internet has an insignificant effect on economic growth in Nigeria.
Another analysis is conducted using internet usage and GDP per capita growth as the independent variables and using the digital financial inclusion indicators as the dependent variable. The GDP per capita growth variable is used as a proxy to measure the level of economic development. The results are reported in columns 7 to 12 of Tables 5 and 6. The MMA coefficient is positively significant in column 7 of Tables 5 and 6. This indicates that increase in the percentage of people using the internet leads to a significant increase in economic growth. In contrast, the EDV coefficient is not significant in columns 7 to 12 of Tables 5 and 6. This indicates that increase in the level of economic development does not have a significant effect on women digital financial inclusion. Similarly, the INT variable has an insignificant effect on the MP, MR, MRP, DD and CC variables in columns 8 to 12 of Tables 5 and 6.
5. Conclusion
This article analysed the trend in women digital financial inclusion in Nigeria using six digital financial inclusion indicators obtained from the global Findex database, such as, the percentage of women who own a mobile money account, the percentage of women who made or received a digital payment, the percentage of women who made a digital payment, the percentage of women who received a digital payment, the percentage of women who own a credit card and the percentage of women who own a debit card. The trend was analysed for the year 2014, 2017 and 2021. The study also analysed the relationship between women digital financial inclusion and economic growth.
The trend analysis showed a sustained, although small, improvement in women mobile money account ownership during the period, while the other indicators witnessed a decrease in 2017 from 2014 and an increase in 2021, except for women credit card ownership which remained at the same level during the period examined.
The regression results showed a significant positive relationship between the digital financial inclusion indicators and economic growth, except for the women mobile money account ownership indicator. The findings also reveal that internet usage has a significant positive effect on women digital financial inclusion in Nigeria. The results remained robust to alternative econometric estimation.
The implication of the findings is that greater women digital financial inclusion can accelerate economic growth in Nigeria. Policymakers should encourage investment in fintech products and improve internet access and usage to increase women digital financial inclusion and economic growth in Nigeria. More investment in fintech and internet access is needed in Nigeria to increase access to digital financial services for women and to increase women’s use of digital devices to receive and make payments. Policymakers and practitioners in Nigeria should also work collaboratively to increase digital financial inclusion for women due to its potential to increase economic growth in Nigeria. There is also a need to create awareness among women about the benefits of using digital financial services particularly the use of credit cards, debit cards and point-of-sale devices for digital payments. This will help to increase women’s use of digital financial services and increase the level of women digital financial inclusion in Nigeria. Policymakers should also partner with fintech and bigtech providers and support them in their efforts to increase digital financial inclusion for women. Financial sector agents should develop gendered financial products and services that are targeted at women. These initiatives would ensure that women digital financial inclusion contributes to economic growth in Nigeria.
The study has two limitations. First, the study used a limited set of digital financial inclusion indicators. Using other indicators of digital financial inclusion could offer new insights. Second, the study is limited by the short sample period. This is due to the short coverage of the data in the global Findex database.
Future research can extend this study by using a longer sample period and a broader set of digital financial inclusion indicators. Future research studies can also examine the effect of digital financial inclusion on several development indicators such as poverty and sustainable development.
Figures
Figure 1
Women digital financial inclusion indicators
Figure 2
Relationship between women mobile money account ownership and economic growth
Figure 3
Relationship between women that made or received payments and economic growth
Figure 4
Relationship between women that made digital payments and economic growth
Figure 5
Relationship between women that received digital payments and economic growth
Figure 6
Relationship between women debit card ownership and economic growth
Figure 7
Relationship between women credit card ownership and economic growth
Indicators of digital financial inclusion and economic growth
| The indicators | Variable | 2014 | 2017 | 2021 |
|---|---|---|---|---|
| Mobile money account, female (% age 15+) | MMA | 2% | 4% | 5% |
| Made or received a digital payment, female (% age 15+) | MRP | 26% | 21% | 23% |
| Made a digital payment, female (% age 15+) | MP | 20% | 17% | 20% |
| Received digital payments, female (% age 15+) | MR | 20% | 16% | 18% |
| Owns a credit card, female | CC | 2% | 2% | 2% |
| Owns a debit card, female | DD | 25% | 23% | 26% |
| Full year GDP growth | GDPR | 6.22% | 0.82% | 3.45% |
Source(s): Global Findex and WDI
Pearson correlation of the variables
| Correlation (p-value) | MMA | MP | MR | MRP | GDPR | DD |
|---|---|---|---|---|---|---|
| MMA | 1.000 | |||||
| – | ||||||
| MP | −0.1889 | 1.000 | ||||
| (0.87) | – | |||||
| MR | −0.654 | 0.866 | 1.000 | |||
| (0.54) | (0.33) | – | ||||
| MRP | −0.737 | 0.802 | 0.993* | 1.000 | ||
| (0.47) | (0.40) | (0.07) | – | |||
| GDPR | −0.255 | −0.901 | −0.563 | −0.465 | 1.000 | |
| (0.83) | (0.28) | (0.61) | (0.69) | – | ||
| DD | 0.142 | 0.944 | 0.654 | 0.563 | −0.993* | 1.000 |
| (0.91) | (0.21) | (0.54) | (0.61) | (0.07) | – |
Note(s): *represents statistical significance at the 10% level. MMA = women who own a mobile money account. MRP = women who made or received a digital payment. MP = women who made a digital payment. MR = women who received a digital payment. CC = women who own a credit card. DD = women who own a debit card. GDPR = real GDP growth
Source(s): Author’s computation
Impact of women digital financial inclusion on economic growth (Two-stage least squares (2SLS) regression)
| GDPR | GDPR | GDPR | GDPR | GDPR | GDPR | |
|---|---|---|---|---|---|---|
| Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | |
| MMA | 0.688 (0.31) | |||||
| MP | 0.181 (0.12) | |||||
| MR | 0.193* (0.10) | |||||
| MRP | 0.272* (0.09) | |||||
| DD | 0.137 (0.13) | |||||
| CC | 1.666 (0.14) | |||||
| J-statistic | 1.531 | 1.132 | 1.964 | 2.000 | 0.506 | 2.289 |
| Prob (J-statistic) | 0.216 | 0.287 | 0.161 | 0.157 | 0.476 | 0.000 |
Note(s): *represents statistical significance at the 10% level. MMA = women who own a mobile money account. MRP = women who made or received a digital payment. MP = women who made a digital payment. MR = women who received a digital payment. CC = women who own a credit card. DD = women who own a debit card. GDPR = real GDP growth
Source(s): Author’s computation
Impact of digital financial inclusion on economic growth (Arellano–Bond First Difference GMM)
| GDPR | GDPR | GDPR | GDPR | GDPR | GDPR | |
|---|---|---|---|---|---|---|
| Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | Coefficient (p-value) | |
| MMA | 0.560 (0.11) | |||||
| MP | 0.180* (0.08) | |||||
| MR | 0.190* (0.07) | |||||
| MRP | 0.146* (0.07) | |||||
| DD | 0.142* (0.08) | |||||
| CC | 1.666* (0.09) | |||||
| J-statistic | 1.067 | 1.147 | 1.345 | 1.006 | 0.926 | 0.456 |
| Prob (J-statistic) | 0.301 | 0.284 | 0.246 | 0.315 | 0.335 | 0.567 |
Note(s): *represents statistical significance at the 10% levels. MMA = women who own a mobile money account. MRP = women who made or received a digital payment. MP = women who made a digital payment. MR = women who received a digital payment. CC = women who own a credit card. DD = women who own a debit card. GDPR = real GDP growth
Source(s): Author’s computation
Further analysis: impact of women digital financial inclusion on economic growth (2SLS estimation)
| Variable | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GDPR | GDPR | GDPR | GDPR | GDPR | GDPR | MMA | MP | MR | MPR | DD | CC | |
| MMA | −1.184 (0.86) | |||||||||||
| MP | 0.353 (0.33) | |||||||||||
| MR | 0.335 (0.32) | |||||||||||
| MRP | 0.252 (0.34) | |||||||||||
| DD | 0.272 (0.38) | |||||||||||
| CC | 2.868 (0.46) | |||||||||||
| INT | 0.002 (0.79) | −0.001 (0.53) | 0.0001 (0.56) | −0.001 (0.59) | −0.001 (0.58) | −0.001 (0.69) | 0.001* (0.07) | 0.004 (0.21) | 0.004 (0.24) | 0.005 (0.24) | 0.006 (0.21) | 0.001 (0.23) |
| EDV | −0.001 (0.60) | 0.018 (0.59) | 0.019 (0.59) | 0.025 (0.59) | 0.020 (0.64) | 0.001 (0.72) | ||||||
| J-statistic | 1.522 | 4.44 | 3.331 | 2.912 | 1.991 | 3.198 | 1.19 | 1.99 | 3.452 | 3.788 | 3.567 | 1.98 |
| Prob (J-statistic) | 0.221 | 0.02 | 0.124 | 0.891 | 0.112 | 0.791 | 0.002 | 0.31 | 2.22 | 2.05 | 1.89 | 0.07 |
Note(s): *represents statistical significance at the 10% level. MMA = women who own a mobile money account. MRP = women who made or received a digital payment. MP = women who made a digital payment. MR = women who received a digital payment. CC = women who own a credit card. DD = women who own a debit card. GDPR = real GDP growth. EDV = GDP per capital growth. INT = percentage of people using the Internet
Source(s): Author’s computation
Further analysis: Impact of women digital financial inclusion on economic growth (GMM estimation)
| Variable | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GDPR | GDPR | GDPR | GDPR | GDPR | GDPR | MMA | MP | MR | MPR | DD | CC | |
| MMA | −1.184 (0.86) | |||||||||||
| MP | 0.353 (0.33) | |||||||||||
| MR | 0.335 (0.32) | |||||||||||
| MRP | 0.252 (0.34) | |||||||||||
| DD | 0.272 (0.38) | |||||||||||
| CC | 2.868 (0.46) | |||||||||||
| INT | 0.002 (0.79) | −0.001 (0.53) | 0.0001 (0.56) | −0.001 (0.59) | −0.001 (0.58) | −0.001 (0.69) | 0.001* (0.05) | 0.004 (0.17) | 0.004 (0.18) | 0.005 (0.19) | 0.006 (0.16) | 0.0004 (0.18) |
| EDV | −0.001 (0.49) | 0.018 (0.48) | 0.019 (0.47) | 0.024 (0.49) | 0.020 (0.53) | 0.001 (0.63) | ||||||
| J-statistic | 1.522 | 4.44 | 3.331 | 2.912 | 1.991 | 3.198 | 4.861 | 4.386 | 4.111 | 4.117 | 4.381 | 4.181 |
| Prob (J-statistic) | 0.221 | 0.02 | 0.124 | 0.891 | 0.112 | 0.791 | 1.44 | 1.521 | 0.121 | 0.551 | 1.51 | 1.33 |
Note(s): *represents statistical significance at the 10% level. MMA = women who own a mobile money account. MRP = women who made or received a digital payment. MP = women who made a digital payment. MR = women who received a digital payment. CC = women who own a credit card. DD = women who own a debit card. GDPR = real GDP growth. EDV = GDP per capital growth. INT = percentage of people using the Internet
Source(s): Author’s computation
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